CHS: Small: Modeling Cyber Transportation and Human Interaction in Connected and Autonomous Vehicles

CHS：小型：对联网和自动驾驶车辆中的网络运输和人机交互进行建模

• 批准号: 1422396
• 负责人: Changxu Wu
• 金额: $ 50万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1422396&HistoricalAwards=false
• 关键词: CHS; Small; Modeling; Cyber; Transportation

The human element will constitute a critical component of tomorrow's Cyber Transportation Systems (CTS), either as drivers interacting with wireless messages in connected vehicle settings or as driver-passengers when vehicles are automated. Given that no engineered system will work perfectly all of the time, this raises important questions relating to the nature of the interaction between CTS and the human driver. Whereas the focus of the current literature has primarily been on hardware and software, in this pioneering project the PI and his research team will instead explore human-CTS interaction as the central design consideration. In accordance with this vision, they will develop and experimentally validate an innovative computational framework (mathematical model) for CTS that quantifies the effects of system design parameters on the key elements of human cognition and performance, which in turn will enable the derivation of design requirements and optimal parameter settings for connected and automated vehicles in order to maximize human safety.For connected vehicles the model could be employed to determine minimal notification requirements (e.g., message transmission reliability) so as to maintain driver alertness and minimize driver distractions. For automated vehicles, the framework could be utilized to derive the minimal acceptable system reliability, optimal re-practice to minimize motor skill decay, and optimal lead time and design of the messages informing a driver to take over control of the vehicle (machine to human driver hand-over). Project outcomes will provide researchers in the field with the first tool to understand the fundamental mechanisms of human-CTS interaction (e.g., the impact of system reliability on human acceptance and trust), by predicting the effects of technology on driver behavior. The software will be open source, so that CTS researchers can easily modify their designs and/or explore the effect of modifying existing features and/or adding new ones as changes in technology may warrant.

人的因素将构成未来网络交通系统（CTS）的关键组成部分，无论是作为驾驶员在联网车辆设置中与无线消息交互，还是作为驾驶员-乘客在车辆自动化时。 考虑到没有一个工程系统会一直完美地工作，这就提出了与CTS和人类驾驶员之间交互性质有关的重要问题。鉴于目前文献的重点主要集中在硬件和软件上，在这个开创性的项目中，PI和他的研究团队将探索人与CTS的交互作为中心设计考虑因素。 根据这一愿景，他们将开发和实验验证一个创新的计算框架CTS的（数学模型），量化了系统设计参数对人类认知和性能关键要素的影响，这反过来将使设计要求和最佳参数设置的连接和自动驾驶车辆的推导，以最大限度地提高人类安全。用于确定最小通知要求（例如，消息传输可靠性），以便保持驾驶员警觉性并使驾驶员分心最小化。 对于自动驾驶汽车，该框架可用于获得最小可接受的系统可靠性，最佳的再练习，以最大限度地减少运动技能衰退，以及最佳的前置时间和消息设计，通知驾驶员接管车辆的控制（机器到人类驾驶员的移交）。 项目成果将为该领域的研究人员提供第一个工具，以了解人类与CTS相互作用的基本机制（例如，系统可靠性对人类接受和信任的影响），通过预测技术对驾驶员行为的影响。 该软件将是开源的，因此CTS研究人员可以很容易地修改他们的设计和/或探索修改现有功能和/或添加新功能的效果，因为技术的变化可能会保证。